Principal component regression, keeping variable names

Hi everyone,

I am performing a principal component analysis in Matlab and I have a problem: as I understand Matlab algorithm for SVD and PCA returns sorted values for eigenvalues and the corresponding eigenvectors, so making it impossible to identify the original data. Since I want a visual formula of my regression to show for an important project and the predictors are at least ten I need to find a way to keep the variable name on each array in order to being able to identify the variables at the end of the principle component regression. I am grateful for anyone who can help in any way.

Diletta

Answer 1

[Bjorn Gustavsson]

Well the eigen-vectors will correspond to some linear combinations of your orignal variables. As such one eigenvector might for example correspond to [0.267*apples, 0.534*oranges, 0.801*pigs/m^2] - depending on what your original variables are...